Secure Average Consensus with Mass Re-Allocation

In recent years, the security and resilience of distributed algorithms have become a feature of utmost importance in the context of Industrial Control Systems. In this paper, we consider a two-level security framework: (i) the level of the interconnected devices in the field, for which we develop a distributed consensus algorithm robust to false data injection attacks; (ii) the upper level of a verifier that poses authentication challenges to the underlying agents. Thanks to the collaboration between the two layers, it is possible to implement a recovery procedure that involves re-allocating the mass of the agent recognized as malicious starting from the last authenticated trustworthy value. This procedure ensures that the consensus algorithm will converge to the correct average of the initial conditions of all agents, despite the presence of attackers. A simulation campaign completes the paper and demonstrates its effectiveness experimentally.